{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import llama_cpp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ggml_init_cublas: GGML_CUDA_FORCE_MMQ:   no\n",
      "ggml_init_cublas: CUDA_USE_TENSOR_CORES: yes\n",
      "ggml_init_cublas: found 1 CUDA devices:\n",
      "  Device 0: NVIDIA GeForce RTX 2060, compute capability 7.5\n"
     ]
    }
   ],
   "source": [
    "llama_cpp.llama_backend_init(numa=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "llama_model_loader: loaded meta data with 16 key-value pairs and 291 tensors from ../../models/mistral-7b-v0.1-GGUF/ggml-model-Q4_K.gguf (version GGUF V2)\n",
      "llama_model_loader: - tensor    0:                token_embd.weight q4_K     [  4096, 32000,     1,     1 ]\n",
      "llama_model_loader: - tensor    1:               output_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor    2:                    output.weight q6_K     [  4096, 32000,     1,     1 ]\n",
      "llama_model_loader: - tensor    3:              blk.0.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor    4:              blk.0.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor    5:              blk.0.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor    6:         blk.0.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor    7:            blk.0.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor    8:            blk.0.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor    9:              blk.0.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   10:           blk.0.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   11:            blk.0.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   12:              blk.1.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   13:              blk.1.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   14:              blk.1.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   15:         blk.1.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   16:            blk.1.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   17:            blk.1.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   18:              blk.1.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   19:           blk.1.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   20:            blk.1.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   21:              blk.2.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   22:              blk.2.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   23:              blk.2.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   24:         blk.2.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   25:            blk.2.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   26:            blk.2.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   27:              blk.2.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   28:           blk.2.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   29:            blk.2.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   30:              blk.3.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   31:              blk.3.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   32:              blk.3.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   33:         blk.3.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   34:            blk.3.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   35:            blk.3.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   36:              blk.3.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   37:           blk.3.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   38:            blk.3.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   39:              blk.4.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   40:              blk.4.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   41:              blk.4.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   42:         blk.4.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   43:            blk.4.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   44:            blk.4.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   45:              blk.4.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   46:           blk.4.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   47:            blk.4.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   48:              blk.5.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   49:              blk.5.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   50:              blk.5.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   51:         blk.5.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   52:            blk.5.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   53:            blk.5.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   54:              blk.5.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   55:           blk.5.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   56:            blk.5.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   57:              blk.6.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   58:              blk.6.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   59:              blk.6.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   60:         blk.6.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   61:            blk.6.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   62:            blk.6.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   63:              blk.6.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   64:           blk.6.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   65:            blk.6.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   66:              blk.7.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   67:              blk.7.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   68:              blk.7.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   69:         blk.7.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   70:            blk.7.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   71:            blk.7.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   72:              blk.7.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   73:           blk.7.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   74:            blk.7.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   75:              blk.8.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   76:              blk.8.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   77:              blk.8.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   78:         blk.8.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   79:            blk.8.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   80:            blk.8.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   81:              blk.8.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   82:           blk.8.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   83:            blk.8.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   84:              blk.9.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   85:              blk.9.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   86:              blk.9.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   87:         blk.9.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   88:            blk.9.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   89:            blk.9.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   90:              blk.9.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   91:           blk.9.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   92:            blk.9.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   93:             blk.10.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   94:             blk.10.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   95:             blk.10.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor   96:        blk.10.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   97:           blk.10.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor   98:           blk.10.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor   99:             blk.10.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  100:          blk.10.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  101:           blk.10.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  102:             blk.11.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  103:             blk.11.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  104:             blk.11.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  105:        blk.11.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  106:           blk.11.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  107:           blk.11.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  108:             blk.11.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  109:          blk.11.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  110:           blk.11.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  111:             blk.12.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  112:             blk.12.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  113:             blk.12.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  114:        blk.12.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  115:           blk.12.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  116:           blk.12.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  117:             blk.12.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  118:          blk.12.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  119:           blk.12.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  120:             blk.13.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  121:             blk.13.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  122:             blk.13.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  123:        blk.13.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  124:           blk.13.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  125:           blk.13.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  126:             blk.13.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  127:          blk.13.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  128:           blk.13.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  129:             blk.14.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  130:             blk.14.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  131:             blk.14.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  132:        blk.14.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  133:           blk.14.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  134:           blk.14.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  135:             blk.14.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  136:          blk.14.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  137:           blk.14.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  138:             blk.15.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  139:             blk.15.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  140:             blk.15.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  141:        blk.15.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  142:           blk.15.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  143:           blk.15.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  144:             blk.15.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  145:          blk.15.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  146:           blk.15.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  147:             blk.16.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  148:             blk.16.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  149:             blk.16.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  150:        blk.16.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  151:           blk.16.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  152:           blk.16.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  153:             blk.16.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  154:          blk.16.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  155:           blk.16.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  156:             blk.17.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  157:             blk.17.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  158:             blk.17.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  159:        blk.17.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  160:           blk.17.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  161:           blk.17.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  162:             blk.17.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  163:          blk.17.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  164:           blk.17.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  165:             blk.18.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  166:             blk.18.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  167:             blk.18.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  168:        blk.18.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  169:           blk.18.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  170:           blk.18.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  171:             blk.18.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  172:          blk.18.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  173:           blk.18.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  174:             blk.19.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  175:             blk.19.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  176:             blk.19.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  177:        blk.19.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  178:           blk.19.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  179:           blk.19.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  180:             blk.19.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  181:          blk.19.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  182:           blk.19.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  183:             blk.20.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  184:             blk.20.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  185:             blk.20.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  186:        blk.20.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  187:           blk.20.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  188:           blk.20.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  189:             blk.20.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  190:          blk.20.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  191:           blk.20.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  192:             blk.21.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  193:             blk.21.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  194:             blk.21.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  195:        blk.21.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  196:           blk.21.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  197:           blk.21.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  198:             blk.21.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  199:          blk.21.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  200:           blk.21.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  201:             blk.22.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  202:             blk.22.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  203:             blk.22.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  204:        blk.22.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  205:           blk.22.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  206:           blk.22.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  207:             blk.22.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  208:          blk.22.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  209:           blk.22.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  210:             blk.23.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  211:             blk.23.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  212:             blk.23.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  213:        blk.23.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  214:           blk.23.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  215:           blk.23.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  216:             blk.23.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  217:          blk.23.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  218:           blk.23.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  219:             blk.24.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  220:             blk.24.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  221:             blk.24.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  222:        blk.24.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  223:           blk.24.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  224:           blk.24.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  225:             blk.24.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  226:          blk.24.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  227:           blk.24.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  228:             blk.25.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  229:             blk.25.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  230:             blk.25.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  231:        blk.25.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  232:           blk.25.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  233:           blk.25.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  234:             blk.25.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  235:          blk.25.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  236:           blk.25.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  237:             blk.26.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  238:             blk.26.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  239:             blk.26.attn_v.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  240:        blk.26.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  241:           blk.26.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  242:           blk.26.ffn_down.weight q4_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  243:             blk.26.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  244:          blk.26.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  245:           blk.26.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  246:             blk.27.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  247:             blk.27.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  248:             blk.27.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  249:        blk.27.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  250:           blk.27.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  251:           blk.27.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  252:             blk.27.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  253:          blk.27.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  254:           blk.27.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  255:             blk.28.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  256:             blk.28.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  257:             blk.28.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  258:        blk.28.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  259:           blk.28.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  260:           blk.28.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  261:             blk.28.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  262:          blk.28.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  263:           blk.28.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  264:             blk.29.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  265:             blk.29.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  266:             blk.29.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  267:        blk.29.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  268:           blk.29.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  269:           blk.29.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  270:             blk.29.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  271:          blk.29.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  272:           blk.29.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  273:             blk.30.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  274:             blk.30.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  275:             blk.30.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  276:        blk.30.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  277:           blk.30.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  278:           blk.30.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  279:             blk.30.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  280:          blk.30.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  281:           blk.30.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  282:             blk.31.attn_q.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  283:             blk.31.attn_k.weight q4_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  284:             blk.31.attn_v.weight q6_K     [  4096,  1024,     1,     1 ]\n",
      "llama_model_loader: - tensor  285:        blk.31.attn_output.weight q4_K     [  4096,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  286:           blk.31.ffn_gate.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  287:           blk.31.ffn_down.weight q6_K     [ 14336,  4096,     1,     1 ]\n",
      "llama_model_loader: - tensor  288:             blk.31.ffn_up.weight q4_K     [  4096, 14336,     1,     1 ]\n",
      "llama_model_loader: - tensor  289:          blk.31.attn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  290:           blk.31.ffn_norm.weight f32      [  4096,     1,     1,     1 ]\n",
      "llama_model_loader: - kv   0:                       general.architecture str     \n",
      "llama_model_loader: - kv   1:                               general.name str     \n",
      "llama_model_loader: - kv   2:                       llama.context_length u32     \n",
      "llama_model_loader: - kv   3:                     llama.embedding_length u32     \n",
      "llama_model_loader: - kv   4:                          llama.block_count u32     \n",
      "llama_model_loader: - kv   5:                  llama.feed_forward_length u32     \n",
      "llama_model_loader: - kv   6:                 llama.rope.dimension_count u32     \n",
      "llama_model_loader: - kv   7:                 llama.attention.head_count u32     \n",
      "llama_model_loader: - kv   8:              llama.attention.head_count_kv u32     \n",
      "llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32     \n",
      "llama_model_loader: - kv  10:                          general.file_type u32     \n",
      "llama_model_loader: - kv  11:                       tokenizer.ggml.model str     \n",
      "llama_model_loader: - kv  12:                      tokenizer.ggml.tokens arr     \n",
      "llama_model_loader: - kv  13:                      tokenizer.ggml.scores arr     \n",
      "llama_model_loader: - kv  14:                  tokenizer.ggml.token_type arr     \n",
      "llama_model_loader: - kv  15:               general.quantization_version u32     \n",
      "llama_model_loader: - type  f32:   65 tensors\n",
      "llama_model_loader: - type q4_K:  193 tensors\n",
      "llama_model_loader: - type q6_K:   33 tensors\n",
      "llm_load_vocab: special tokens definition check successful ( 259/32000 ).\n",
      "llm_load_print_meta: format           = GGUF V2\n",
      "llm_load_print_meta: arch             = llama\n",
      "llm_load_print_meta: vocab type       = SPM\n",
      "llm_load_print_meta: n_vocab          = 32000\n",
      "llm_load_print_meta: n_merges         = 0\n",
      "llm_load_print_meta: n_ctx_train      = 4096\n",
      "llm_load_print_meta: n_embd           = 4096\n",
      "llm_load_print_meta: n_head           = 32\n",
      "llm_load_print_meta: n_head_kv        = 8\n",
      "llm_load_print_meta: n_layer          = 32\n",
      "llm_load_print_meta: n_rot            = 128\n",
      "llm_load_print_meta: n_gqa            = 4\n",
      "llm_load_print_meta: f_norm_eps       = 0.0e+00\n",
      "llm_load_print_meta: f_norm_rms_eps   = 1.0e-05\n",
      "llm_load_print_meta: f_clamp_kqv      = 0.0e+00\n",
      "llm_load_print_meta: f_max_alibi_bias = 0.0e+00\n",
      "llm_load_print_meta: n_ff             = 14336\n",
      "llm_load_print_meta: freq_base_train  = 10000.0\n",
      "llm_load_print_meta: freq_scale_train = 1\n",
      "llm_load_print_meta: model type       = 7B\n",
      "llm_load_print_meta: model ftype      = mostly Q4_K - Medium\n",
      "llm_load_print_meta: model params     = 7.24 B\n",
      "llm_load_print_meta: model size       = 4.07 GiB (4.83 BPW) \n",
      "llm_load_print_meta: general.name   = LLaMA v2\n",
      "llm_load_print_meta: BOS token = 1 '<s>'\n",
      "llm_load_print_meta: EOS token = 2 '</s>'\n",
      "llm_load_print_meta: UNK token = 0 '<unk>'\n",
      "llm_load_print_meta: LF token  = 13 '<0x0A>'\n",
      "llm_load_tensors: ggml ctx size =    0.10 MB\n",
      "llm_load_tensors: using CUDA for GPU acceleration\n",
      "llm_load_tensors: mem required  =   70.41 MB\n",
      "llm_load_tensors: offloading 32 repeating layers to GPU\n",
      "llm_load_tensors: offloading non-repeating layers to GPU\n",
      "llm_load_tensors: offloaded 35/35 layers to GPU\n",
      "llm_load_tensors: VRAM used: 4095.05 MB\n",
      ".................................................................................................\n"
     ]
    }
   ],
   "source": [
    "params = llama_cpp.llama_model_default_params()\n",
    "params.n_gpu_layers = 35\n",
    "model = llama_cpp.llama_load_model_from_file(\n",
    "    b\"../../models/mistral-7b-v0.1-GGUF/ggml-model-Q4_K.gguf\", params=params\n",
    ")  # Update this to whatever"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 1014, 2936, 9060, 285, 1142]\n",
      "58\n"
     ]
    }
   ],
   "source": [
    "n_ctx = 512\n",
    "n_len = 32\n",
    "n_parallel = 2\n",
    "prompt = b\"The quick brown fox\"\n",
    "\n",
    "tokens = (llama_cpp.llama_token * n_ctx)()\n",
    "tokens_len = llama_cpp.llama_tokenize(\n",
    "    model, prompt, len(prompt), tokens, len(tokens), True, True\n",
    ")\n",
    "print(tokens[:tokens_len])\n",
    "\n",
    "n_kv_req = tokens_len + (n_len - tokens_len) * n_parallel\n",
    "print(n_kv_req)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "llama_new_context_with_model: n_ctx      = 58\n",
      "llama_new_context_with_model: freq_base  = 10000.0\n",
      "llama_new_context_with_model: freq_scale = 1\n",
      "llama_kv_cache_init: offloading v cache to GPU\n",
      "llama_kv_cache_init: offloading k cache to GPU\n",
      "llama_kv_cache_init: VRAM kv self = 7.25 MB\n",
      "llama_new_context_with_model: kv self size  =    7.25 MB\n",
      "llama_build_graph: non-view tensors processed: 740/740\n",
      "llama_new_context_with_model: compute buffer total size = 10.63 MB\n",
      "llama_new_context_with_model: VRAM scratch buffer: 4.51 MB\n",
      "llama_new_context_with_model: total VRAM used: 4106.81 MB (model: 4095.05 MB, context: 11.76 MB)\n"
     ]
    }
   ],
   "source": [
    "ctx_params = llama_cpp.llama_context_default_params()\n",
    "ctx_params.seed = 1234\n",
    "ctx_params.n_ctx = n_kv_req\n",
    "ctx_params.n_batch = max(n_len, n_parallel)\n",
    "ctx_params.n_threads = 1\n",
    "ctx_params.n_threads_batch = 1\n",
    "ctx = llama_cpp.llama_new_context_with_model(model, ctx_params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_ctx = llama_cpp.llama_n_ctx(ctx)\n",
    "batch = llama_cpp.llama_batch_init(max(tokens_len, n_parallel), 0, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ctypes\n",
    "\n",
    "batch.n_tokens = tokens_len\n",
    "for i in range(tokens_len):\n",
    "    batch.token[i] = tokens[i]\n",
    "    batch.pos[i] = i\n",
    "    batch.seq_id[i][0] = 0\n",
    "    batch.n_seq_id[i] = 1\n",
    "    batch.logits[i] = False\n",
    "\n",
    "batch.logits[batch.n_tokens - 1] = True\n",
    "\n",
    "if llama_cpp.llama_decode(ctx, batch) != 0:\n",
    "    print(\"Error decoding\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(n_parallel):\n",
    "    llama_cpp.llama_kv_cache_seq_cp(ctx, 0, i, 0, batch.n_tokens)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7\n",
      "[' j', ' jumped']\n",
      "8\n",
      "[' jumps', ' jumped over']\n",
      "9\n",
      "[' jumps over', ' jumped over the']\n",
      "10\n",
      "[' jumps over the', ' jumped over the lazy']\n",
      "11\n",
      "[' jumps over the lazy', ' jumped over the lazy dog']\n",
      "12\n",
      "[' jumps over the lazy dog', ' jumped over the lazy dog.']\n",
      "13\n",
      "[' jumps over the lazy dog.', ' jumped over the lazy dog.\\n']\n",
      "14\n",
      "[' jumps over the lazy dog.\\n', ' jumped over the lazy dog.\\n\\n']\n",
      "15\n",
      "[' jumps over the lazy dog.\\n\\n', ' jumped over the lazy dog.\\n\\nThe']\n",
      "16\n",
      "[' jumps over the lazy dog.\\n\\nI', ' jumped over the lazy dog.\\n\\nThe quick']\n",
      "17\n",
      "[' jumps over the lazy dog.\\n\\nI’', ' jumped over the lazy dog.\\n\\nThe quick brown']\n",
      "18\n",
      "[' jumps over the lazy dog.\\n\\nI’m', ' jumped over the lazy dog.\\n\\nThe quick brown f']\n",
      "19\n",
      "[' jumps over the lazy dog.\\n\\nI’m not', ' jumped over the lazy dog.\\n\\nThe quick brown fox']\n",
      "20\n",
      "[' jumps over the lazy dog.\\n\\nI’m not sure', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped']\n",
      "21\n",
      "[' jumps over the lazy dog.\\n\\nI’m not sure if', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped over']\n",
      "22\n",
      "[' jumps over the lazy dog.\\n\\nI’m not sure if that', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped over the']\n",
      "23\n",
      "[' jumps over the lazy dog.\\n\\nI’m not sure if that’', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped over the lazy']\n",
      "24\n",
      "[' jumps over the lazy dog.\\n\\nI’m not sure if that’s', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped over the lazy dog']\n",
      "25\n",
      "[' jumps over the lazy dog.\\n\\nI’m not sure if that’s the', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped over the lazy dog.']\n",
      "26\n",
      "[' jumps over the lazy dog.\\n\\nI’m not sure if that’s the most', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped over the lazy dog.\\n']\n",
      "27\n",
      "[' jumps over the lazy dog.\\n\\nI’m not sure if that’s the most famous', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped over the lazy dog.\\n\\n']\n",
      "28\n",
      "[' jumps over the lazy dog.\\n\\nI’m not sure if that’s the most famous sentence', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped over the lazy dog.\\n\\nThe']\n",
      "29\n",
      "[' jumps over the lazy dog.\\n\\nI’m not sure if that’s the most famous sentence in', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped over the lazy dog.\\n\\nThe quick']\n",
      "30\n",
      "[' jumps over the lazy dog.\\n\\nI’m not sure if that’s the most famous sentence in the', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped over the lazy dog.\\n\\nThe quick brown']\n",
      "31\n",
      "[' jumps over the lazy dog.\\n\\nI’m not sure if that’s the most famous sentence in the English', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped over the lazy dog.\\n\\nThe quick brown f']\n",
      "32\n",
      "[' jumps over the lazy dog.\\n\\nI’m not sure if that’s the most famous sentence in the English language', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped over the lazy dog.\\n\\nThe quick brown fox']\n"
     ]
    }
   ],
   "source": [
    "import ctypes\n",
    "\n",
    "streams = [\"\"] * n_parallel\n",
    "i_batch = [batch.n_tokens - 1] * n_parallel\n",
    "\n",
    "n_cur = batch.n_tokens\n",
    "n_decode = 0\n",
    "\n",
    "while n_cur <= n_len:\n",
    "    batch.n_tokens = 0\n",
    "    for i in range(n_parallel):\n",
    "        if i_batch[i] < 0:\n",
    "            continue\n",
    "\n",
    "        n_vocab = llama_cpp.llama_n_vocab(model)\n",
    "        logits = llama_cpp.llama_get_logits_ith(ctx, i_batch[i])\n",
    "\n",
    "        candidates = (llama_cpp.llama_token_data * n_vocab)()\n",
    "\n",
    "        for token_id in range(n_vocab):\n",
    "            candidates[token_id].id = token_id\n",
    "            candidates[token_id].logit = logits[token_id]\n",
    "            candidates[token_id].p = 0.0\n",
    "\n",
    "        candidates_p = llama_cpp.llama_token_data_array(\n",
    "            candidates, len(candidates), False\n",
    "        )\n",
    "\n",
    "        top_k = 40\n",
    "        top_p = 0.9\n",
    "        temp = 0.4\n",
    "\n",
    "        llama_cpp.llama_sample_top_k(ctx, ctypes.byref(candidates_p), top_k, 1)\n",
    "        llama_cpp.llama_sample_top_p(ctx, ctypes.byref(candidates_p), top_p, 1)\n",
    "        llama_cpp.llama_sample_temp(ctx, ctypes.byref(candidates_p), temp)\n",
    "\n",
    "        new_token_id = llama_cpp.llama_sample_token(ctx, ctypes.byref(candidates_p))\n",
    "\n",
    "        if new_token_id == llama_cpp.llama_token_eos(ctx) or n_cur == n_len:\n",
    "            i_batch[i] = -1\n",
    "            continue\n",
    "\n",
    "        buf = (ctypes.c_char * 32)()\n",
    "        outlen = llama_cpp.llama_token_to_piece(model, new_token_id, buf, len(buf))\n",
    "        streams[i] += bytes(buf[:outlen]).decode(\"utf-8\")\n",
    "\n",
    "        batch.token[batch.n_tokens] = new_token_id\n",
    "        batch.pos[batch.n_tokens] = n_cur\n",
    "        batch.seq_id[batch.n_tokens][0] = i\n",
    "        batch.n_seq_id[batch.n_tokens] = 1\n",
    "        batch.logits[batch.n_tokens] = True\n",
    "\n",
    "        i_batch[i] = batch.n_tokens\n",
    "        batch.n_tokens += 1\n",
    "        n_decode += 1\n",
    "\n",
    "    if batch.n_tokens == 0:\n",
    "        break\n",
    "\n",
    "    n_cur += 1\n",
    "\n",
    "    if llama_cpp.llama_decode(ctx, batch) != 0:\n",
    "        print(\"Error decoding\", flush=True)\n",
    "        break\n",
    "    print(n_cur)\n",
    "    print(streams)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[' jumps over the lazy dog.\\n\\nI’m not sure if that’s the most famous sentence in the English language', ' jumped over the lazy dog.\\n\\nThe quick brown fox jumped over the lazy dog.\\n\\nThe quick brown fox']\n"
     ]
    }
   ],
   "source": [
    "print(streams)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "llama_cpp.llama_batch_free(batch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "llama_cpp.llama_free(ctx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "llama_cpp.llama_free_model(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "llama_cpp.llama_backend_free()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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